Uplink packet scheduling in the presence of interference cancellation in multi‐rate wireless CDMA networks
Bibliographic record
Abstract
Abstract We consider packet scheduling and rate assignment on the uplink of a packet data wireless CDMA network in the presence of imperfect interference cancellation (IC) and limited user transmission rates, and subject to in‐cell and out‐of‐cell resource limitations. The objective is to propose and implement a system level position‐based flow control algorithm that accounts for a limited IC capability provided by power control for multi‐user detection. The proposed algorithm assigns packets to be transmitted to separate queues, one for each spatial zone within which packets generate roughly the same in‐cell interference and impose equal interference on a neighboring base station. Given the cell partitioning into zones, the algorithm dynamically adapts to the resource constraints and efficiently uses IC to provide for fairness in serving the various queues without giving up the objective of maximizing data throughput. Throughput and fairness are the two conflicting objectives to be optimized. We show that the joint use of IC and location‐based scheduling is able to achieve complete fairness with negligible loss in throughput even under stringent resource limitations. The IC technique implemented is based on the interference subspace rejection (ISR) technique. We investigate both successive and group cancellation modes of ISR. Through the zone‐based grouping of users, the flow control algorithm provides a high flexibility in taking advantage of IC and is general enough to adapt to situations with constraints on the transmission rates. Results provided show how group‐based scheduling with group‐cancellation can provide for high fairness even under stringent out‐of‐cell resource limitations. Copyright © 2003 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".